Ultra-sensitive optical fiber SPR biosensor for assisted diagnosis of prostate cancer by label-free detection of miRNA-21

Background Efficient and rapid identification of trace amounts of microRNA-21 (miRNA-21), an oncogenic miRNA, is conducive to the early diagnosis of prostate cancer. Despite extensive research efforts, the development of biosensors capable of achieving clinically relevant sensitivity and limits of detection (LOD) remains challenging, primarily due to the ultralow physiological concentrations of cancer biomarkers in human biological systems. Beyond that, the suboptimal probe designs such as complex sensing structures and unstable sensing materials collectively lead to inadequate repeatability and stability for clinical application. Results Hence, in this work, a label-free and highly sensitive optical fiber Surface Plasmon Resonance (SPR) biosensor with ultralow LOD was developed for detecting miRNA-21, which was fabricated simply by coating a layer of Au film and gold nanoparticles (AuNPs) onto a multimode-single-mode-multimode (MSM) optical fiber, and then biofunctionalized with optimized single-stranded DNA (ssDNA) enabling the quantification of miRNA-21. Excitingly, the biosensors, which have a simple composition and demonstrated with excellent linearity, specificity and stability, were experimentally verified to reach an ultra-low LOD of 1.86 × 10 –19  M that significantly lower than current detection method and high sensitivity of 3021.48 RIU/nm. And detection of trace miRNA-21 was enabled without RNA amplification. The sensor's capability to effectively differentiate prostate cancer patients from healthy controls was demonstrated by testing clinical serum samples and the sensor achieved higher detection accuracy compared to the commonly used clinical prostate-specific antigen (PSA) quantification. Significance The proposed sensing platform processes the merits of simple configuration as well as low cost and has potential to auxiliary early-stage diagnosis of various cancers by detecting associated biomarkers.